rfPermute

Description

rfPermute estimates the significance of importance metrics for a Random Forest model by permuting the response variable. It will produce null distributions of importance metrics for each predictor variable and p-value of observed. The package also includes several summary and visualization functions for randomForest and rfPermute results.

version 2.1.1

version 2.0.1

Fixed bug in plot.rfPermute that was reporting the p-value incorrectly at the top of the figure.

Fixed multi-threading in rfPermute so it works on Windows too.

Added impHeatmap function.

Switched proximity.plot to use ggplot2 graphics.

version 2.0

Fixed bug with calculation of p-values not respecting importance measure scaling (division by standard deviations). New format of output of rfPemute has separate $null.dist and $pval elements, each with results for unscaled and scaled importance mesures. See ?rfPermute for more information.

rp.importance and plot.rfPermute now take a scale argument to specify whether or not importance values should be scaled by standard deviations.

If nrep = 0 for rfPermute, a randomForest object is returned.

version 1.9.3

Fixed import declarations to avoid grid name clashes.

Fixed logic error in clean.rf.data where fixed predictors were not removed.

Fixed error in use of main argument in plot.rp.importance.

version 1.9.2

Added this NEWS.md

Added README.md

Added num.cores argument to rfPermute to take advantage of multi-threading